code: def __init__(self, x1, x2, kernel, last_dim_is_batch=False, **params):
      super(LazyEvaluatedKernelTensor, self).__init__(
          x1,
          x2,
          kernel=kernel,
          last_dim_is_batch=last_dim_is_batch,
          **params,
      )
      self.kernel = kernel
      self.x1 = x1
      self.x2 = x2
      self.last_dim_is_batch = last_dim_is_batch
      self.params = params
      self._is_grad_enabled = torch.is_grad_enabled()
  
imports: import functools
  from typing import Callable
  import torch
  from linear_operator import LinearOperator, to_linear_operator
  from linear_operator.utils.getitem import _noop_index
  from ..None import beta_features, settings
  from ..utils import deprecation
  from ..utils.memoize import cached
label_desc: Use image node_id 2 to create a new LazyEvaluatedKernelTensor object from inherited base classes: LinearOperator with example: obj = LazyEvaluatedKernelTensor(x1, x2, kernel, last_dim_is_batch)